Causal networks and their toolkit in kse

Jianming Liang, Qinliang Ren, Zhuoqun Xu, Jiaqing Fang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Causal Networks have recently received much attention in AI, and have been used in many areas as a knowledge representation. First, from the knowledge engineering point of view, we present causal networks, introduce a concept of network parameters, propose some principles for construction and use of causal networks, and indicate the advantages of the knowledge bases with the form of causal networks. In order to put them into practice and incorporate with other techniques in AI, we have introduced the idea of causal networks into a Knowledge System Environment (KSE) as a toolkit (Bent). Then we give an overview of KSE, followed by a detailed discussion about Bent.

Original languageEnglish (US)
Pages (from-to)139-148
Number of pages10
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume945
StatePublished - Jan 1 2014
Externally publishedYes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Causal networks and their toolkit in kse'. Together they form a unique fingerprint.

  • Cite this